Research on audio recognition and processing based on MLP model
Chuxin Hang, Mandan Zhuang, Tongyuan Bai, Peng Yuan, Kang Sun · 2022
This article is based on deep learning theory and big data technology to build a model on how to analyse massive amounts of audio data and use it to provide better services. Firstly, the spectrograms and waveforms are visualised to initially analyse the audio features. Then, the MFCC and Chroma features of audio were extracted respectively, and the MLP model was built to classify the two features and trained separately. In order to make the audio recognition technique highly efficient, this paper also adopts the non-negative matrix decomposition method (NMF) to enhance the audio data, which makes the differentiation between different audio data more significant, and the accuracy of the MLP model built based on the reconstructed new audio data finally reaches 89.12%.